/// <summary>
/// Create a <see cref="CategoricalImputerEstimator"/>, which fills in the missing values in a column with the most frequent value.
/// Supports Floats, Doubles, and Strings.
/// A string is assumed "missing" if it is empty.
/// </summary>
/// <param name="catalog">Transform Catalog</param>
/// <param name="columns">List of <see cref="InputOutputColumnPair"/> to fill in missing values</param>
/// <returns><see cref="CategoricalImputerEstimator"/></returns>
public static CategoricalImputerEstimator ImputeCategories(this TransformsCatalog catalog, params InputOutputColumnPair[] columns)
{
var options = new CategoricalImputerEstimator.Options
{
Columns = columns.Select(x => new CategoricalImputerEstimator.Column
{
Name = x.OutputColumnName, Source = x.InputColumnName ?? x.OutputColumnName
}).ToArray(),
};
return(new CategoricalImputerEstimator(CatalogUtils.GetEnvironment(catalog), options));
}
/// <summary>
/// Create a <see cref="CategoricalImputerEstimator"/>, which fills in the missing values in a column with the most frequent value.
/// Supports Floats, Doubles, and Strings.
/// A string is assumed "missing" if it is empty.
/// </summary>
/// <param name="catalog">Transform Catalog</param>
/// <param name="outputColumnName">Output column name</param>
/// <param name="inputColumnName">Input column name, if null defaults to <paramref name="outputColumnName"/></param>
/// <returns><see cref="CategoricalImputerEstimator"/></returns>
public static CategoricalImputerEstimator ImputeCategories(this TransformsCatalog catalog, string outputColumnName, string inputColumnName = null)
{
var options = new CategoricalImputerEstimator.Options
{
Columns = new CategoricalImputerEstimator.Column[1] {
new CategoricalImputerEstimator.Column()
{
Name = outputColumnName, Source = inputColumnName ?? outputColumnName
}
}
};
return(new CategoricalImputerEstimator(CatalogUtils.GetEnvironment(catalog), options));
}
public static CommonOutputs.TransformOutput ImputeToKey(IHostEnvironment env, CategoricalImputerEstimator.Options input)
{
var h = EntryPointUtils.CheckArgsAndCreateHost(env, CategoricalImputerTransformer.ShortName, input);
var xf = new CategoricalImputerEstimator(h, input).Fit(input.Data).Transform(input.Data);
return(new CommonOutputs.TransformOutput()
{
Model = new TransformModelImpl(h, xf, input.Data),
OutputData = xf
});
}
